Biology 107
General Biology
Lab 4: Using the Scientific Method
You have all asked questions, developed educated predictions, and even put your predictions to the test. In
some laboratory exercises this semester, we will do this in a more rigorous way and call it the scientific method.
You will use the scientific method to explore a variety of biological principles. As scientists, you will work in
research teams, collaborating as you ask questions and solve problems. Before you begin to examine biological
principles, you need to have a firm grasp of the scientific method. This laboratory is designed to introduce the
main types of thinking involved in how a biologist attacks a problem.
Objectives
The six steps involved in the scientific method are:
When you have successfully completed this lab,
you should be able to:
1) Observe nature
2) Ask questions
3) Formulate testable hypotheses
4) Conduct experiments to test these hypotheses
5) Make conclusions based on your experimental
results
6) Formulate new, testable hypotheses based on your
conclusions
1. Use the scientific method and understand which
types of questions can be answered through scientific
investigation.
2. Explain what characterizes a good scientific hypothesis.
3. Use experimental data to evaluate an hypothesis.
4. Write the Discussion section of a lab report.
We will also practice writing, data analysis and
presentation skills introduced in earlier laboratory
exercises.
Introduction
In the words of Vincient Dethier, a prominent insect
physiologist, anyone can be a biologist - “Anyone
with a genuine love of nature, an insatiable curiosity
about life, a soaring imagination, devilish ingenuity,
the patience of Job and the ability to read has the basic
ingredients and most of the necessary accouterments
to become a first class biologist” - in other words,
you! After all, science is really little more than curiosity and common sense which assumes that biological
systems are understandable.
© 2002, University of Evansville Biology Department
Procedures
Section A - Questions and Hypotheses
1. Observe Nature
Science usually starts with observations of the natural world and makes generalizations from these observations. You have all observed animals and plants
in nature, but now it’s time to get quantitative. Our
observations are going to require measurements. Each
measurement consists of a number and a unit, like
“six feet.” Units, also called dimensions, can describe
number of individuals, time, length, mass, temperature, and many other quantities. Speed, for instance,
has the dimensions of length per unit time, so we talk
about speeds with units of meters/second, miles/hour
or furlongs/fortnight. Once you know what to measure, you gain insight into how to measure it. Consider
speed again. Because its dimensions are length and
time, you would need a ruler and stopwatch. Much of
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the fun of designing a good experiment is determining
how to measure the critical variables.
2. Ask Questions
Scientists are curious individuals whose curiosity
is focused on understanding the natural world. They
use previous research or personal observations of natural phenomena as a basis for asking questions about
the underlying causes or reasons for these phenomena. For a question to be pursued by scientists, the
phenomenon must be well defined and repeatable.
The variables involved must be measurable.
There are limits to the ability of science to answer
questions. Consider, for example, this question: Do
high temperatures cause people to behave immorally?
Can a scientist investigate this question? Temperature
is well defined and measurable, but what is “moral
behavior?” Is it measurable? Could people even
agree on a definition of the term? Until “moral behavior” is defined, there are no experiments that could be
designed to test this question. Which of the following questions do you think can be answered scientifically?
1. Does exposure to coal dust in mines cause an
increase in respiratory disease?
2. Does good nutrition lead to increased growth in
cattle?
3. Was Napoleon superstitious?
4. Do cactus spines deter herbivores?
5. Was the malignant tumor that was found in the
lungs of a 70 year old woman caused by living
with her chain-smoking husband for 50 years?
As you read and prepare to come to lab, jot down a
few notes regarding the questions above for class discussion. How did you decide if these questions could
be answered scientifically? For which of these above
statements could you formulate a well defined, testable hypothesis? For each of the answerable questions, write a testable hypothesis (after reading the
next paragraphs). Volunteers will read their hypotheses in class.
3. Formulate Testable Hypotheses
Scientists try to answer questions by suggesting
possible explanations. Hypotheses are simply tentative explanations which could account for observed
phenomena. Formulating testable hypotheses draws
heavily upon the scientist’s creativity and imagination. A hypothesis can be described as a logical link
between if and then. Consider question #4 above,
“Do cactus spines deter herbivores?” One hypothesis based on this question might be “If the spines are
removed from cacti, then herbivores will still not eat
the cacti.”
A scientifically useful hypothesis must be testable
and falsifiable (able to be proved false). To satisfy
the requirement that an hypothesis be falsifiable, it
must be possible for the test results to contradict the
hypothesis. In our example, if spines are removed
from test cacti and the plants are eaten by animals,
then the hypothesis has been proved false or falsified.
Even though the hypothesis can be falsified, it
can never be proved true. This is a very important
point. The evidence from an investigation can only
provide support for the hypothesis. If our cacti without spines were not eaten, then the hypothesis has not
been proved, but it has been supported by the evidence. Other explanations still must be excluded and
new evidence from additional experiments and observations might falsify this hypothesis at a later date.
(Perhaps the herbivores weren’t hungry.) In science,
a single experiment rarely provides results that clearly
support or falsify the hypothesis. In most cases, the
evidence serves to modify the hypothesis or the conditions of the experiment.
Scientists often propose and reject a variety of
hypotheses before they design a single test. Examine
the following statements and note which would be
useful as scientific hypotheses and could be investigated using scientific procedures. Give the reason for
each of your answers by stating whether it could be
falsified and which factors are measurable and controllable.
1. Male seahorses incubate the eggs to give the tired
females a chance to rest.
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2. Students who sit in the front of the classroom get
better grades than those who sit in the back.
3. In nutrient-poor soils, sulfur dioxide pollution
results in increased growth in soybeans.
4. Dinosaurs became extinct because a supernatural
power was dissatisfied with their progress.
5. Humans first inhabited North American about
12,000 years ago.
The class will discuss these ideas, so make notes to
prepare for the discussion.
Section B - Experimental Design
Designing an experiment to test your hypothesis
is the most creative aspect of science. Many times
scientists think of interesting questions that can’t be
answered or experiments that are impractical. Examples: “ Does heat increase immorality” or “What percent of all women over 25 have tumors observable by
CAT scan? “ Other ideas might never receive approval
from the animal rights committees. “Does sacrificing
a bull by throwing it into a volcano decrease the lava
flow during the eruption?”
Scientists usually design, critique, and modify an
experiment before they commit the time and resources
to perform it. Designing an experiment begins with
defining variables. The investigator generally manipulates one or more variables, minimizes variation in
other variables, and measures responses in a third set
of variables. Variables that are manipulated by the
investigator are independent variables. Variables
that are held constant are known as fixed variables,
and variables that measure responses to the experiment are dependent variables.
Dependent variables are the responses to the
experiment. For example, if a scientist investigates
the ability of a new fertilizer to increase growth of
soybeans, the height of the plants or the weight of the
seeds produced by the plants are dependent variables.
Last week, the dependent variable was the amount of
water which entered each sucrose solution by osmosis. It was what you measured.
Independent variables are controlled by the investigator, and are changed to evaluate how the dependent
variables will respond. In the soybean experiment,
the amount of fertilizer applied to the plant is the
independent variable. It is the factor that you, the
experimenter, manipulated. Frequently, independent
variables can be divided into two subsets: the control
treatment, and the experimental treatment(s). The
control is usually a standard or baseline treatment to
which the experimental treatment is compared. Often
the control treatment differs from the experimental
treatment by the complete absence of the independent
variable in the control condition. Thus, in the soybean
experiment, plants with no fertilizer applied would
be the control. The experimental treatments would be
treatments in which the variable is present at some
level. In this case, the amount of fertilizer applied
might be 5, 10 and 15 units per plot. In the osmosis
lab, the independent variable was the concentration
of sucrose in the various solutions and the control
solution was the one which contained 100% distilled
water (no sucrose).
In all experiments, there are many fixed variables.
These are variables that might affect the dependent
variable, but are not of interest in the hypothesis.
For example, in the soybean experiment, the scientist
wants to know how a new fertilizer affects growth of
soybeans. The experimenter is not interested in how
watering affects growth of soybeans, but because it is
well known that the amount of water given to a plant
strongly affects the growth of the plant, it is important
for each plant to receive the same amount of water.
Thus, water is a fixed variable in this example.
Fixed variables last week in your osmosis experiment included which balance was used to weigh the
sucrose-containing bags, the volume of water added to
each beaker, and which student blotted and weighed
each solution, etc. Think about the potential weight
variations you could have produced if one student in
your group always neglected to blot the dialysis bag
before weighing and another student blotted the bag
properly. This fixed variable is not an important part
of your hypothesis, but it is a variable you must control. Before weighing, each bag must be treated identically.
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Prepare for class discussion by thinking about
these questions:
1. What other fixed variables should the soybean
scientist include?
2. What is an example of a variable that is completely irrelevant, and is neither fixed nor dependent nor independent?
3. What does a fixed variable become if the scientist
decides to also manipulate its conditions?
4. What is a placebo?
Then, analyze the following experiment. Identify
independent, dependent, and fixed variables. Is there
a problem in the experimental design?
Dr. Chaleb intends to study the effects of
household bleach on various items of laundry. He plans to wash clothing items in a
Maytag washer without bleach, and compare their color to other items of clothing
washed in a Kenmore washer which automatically adds bleach. The items will be
compared to determine whether bleach
reduces brightness of colors.
Identify:
Independent variable
Dependent variable
Fixed variables
Is there a problem in the experimental design?
Explain your answer.
One of the most difficult questions to answer when
designing an experiment is how many samples, or
replicates, to take. Generally, the same procedure will
not produce exactly the same results each time it is
run. If you take too many samples, you may be wasting time, materials and money. On the other hand, if
you take too few samples, it may be difficult to draw
any meaningful conclusions from your results. Sampling is a compromise between accuracy and effort,
and scientists often find that they do not take enough
samples because of their failure to plan ahead. In our
biology laboratory you will find that the sample sizes
of experiments will be greatly influenced by lab time,
materials, space and whether or not you have taken
the time to read your instructions thoroughly ahead of
time. In Biology 107 experiments, a minimum of
three trials is required. Students are encouraged
to improve their lab report, and therefore their
grade, by using more than three trials.
Section C - Analyzing Your Results
Every good experiment produces data. Generally,
you cannot just look over the raw data and decide
whether the hypothesis is supported or rejected.
Instead, the data must be condensed into a form that
can be used to evaluate the hypothesis. Scientists
commonly use three different ways of condensing and
presenting numeric data: graphs, tables, and statistical tests. You were introduced to some basics of data
analysis in the Excel data lab. Now, we will extend
our discussion of how to understand the data from an
experiment.
Descriptive statistics summarize, organize, and
simplify data. They measure either the central tendency (e.g., mean) or the spread of the values (e.g.,
standard deviation). There are three different metrics
that measure central tendency of a dataset.
Median
If all observations are arranged in rank order from
smallest to largest, the median is that value with 50%
of the observations above it and 50% of the observations below it.
Mean ( x )
The arithmetic average of all observations.
Most people are familiar with means, which are
calculated by adding all of the values and dividing
by the sample size. Medians are less widely known,
but also measure central tendency; they can be very
important, particularly if data sets are skewed. For
example, if Bill Gates joined the laboratory session
today, the mean income would change dramatically
but the median would not change much.
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When data represent samples of a population, or
are independent estimates of a quantity, it is necessary to have a representative sample and avoid error
resulting from small sample size. Recall our fertilizer experiment and imagine what you would think if
the first time you used a new fertilizer you saw a 25%
increase in the number of bean pods produced and
the second time your increase was 3%. Would you
average the two percentages and develop an advertising campaign to sell the new fertilizer saying it
would produce a 14% increase in yields? Or would
you run the experiment several more times to get a
more accurate estimate of the actual increase in yield?
What would you do if your next trial showed a 27%
increase?
The measures of variability that we will be concerned with are:
Range
The difference between the smallest and largest value
in a distribution of values
Standard Deviation
(S.D.) The deviation of the data from the mean.
Recall that the formula for finding the standard deviation is:
S. D. =
Σ (xi - x)2
Graphs are visual depictions of data or of variable
metrics. As discussed in the Excel data lab, there are
two main types of graphs used in Biology 107: scatter plots and column graphs. Occasionally you may
have reason to use a line graph (a variation of a scatter plot where the points are connected). A review of
the Excel lab will remind you that graphs depict the
independent variable on the horizontal (x) axis, and
the dependent variable on the vertical (y) axis. Every
graph should have labeled axes, the axis scale clearly
shown, and a title explaining what the graph depicts.
Scatter plots are plots of individual, unconnected
data points. These graphs will visually show both
central tendencies and scatter around the central tendencies, but are often misinterpreted. They can
show relationships between two variables without the
requirement that one variable is an independent variable. Recall the scatter plots you generated in Lab #2.
When you constructed a graph with height and forearm length, you did not have a dependent/independent
relationship.
Scatterplot goes here
(n - 1)
n = the number of trials or samples taken
Σ = the summation of all trials
x = the mean or arithmetic average
xi = the observed value that you measured
Although you always want to maximize the number
of trials, to calculate the standard deviation (S.D.),
you must have a minimum of three trials. If you have
time, you may want to run more trials.
Column graphs show a separate bar for each condition of the experimental variable. The height of the
bar is the mean of the dependent variable, and the
standard deviation should almost always be included
as a separate bar or T-shape on top of the bar representing the mean. An important difference between
scatter and column graphs is that line graphs imply a
continuous linear change between the condition of the
independent variable, whereas column graphs do not.
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For example, there is no intermittent stage between
males and females. A column graph is appropriate to
display the data shown below.
table. Look at the table on page 28 of your textbook.
Above the table is a label “Table 2.1”. There is a title
or heading at the top of the table, “Naturally Occurring
Elements in the Human Body”, which describes what
will be found on the table. Like figures, the tables in
a scientific paper should be numbered consecutively.
Section D - Conclusions and Discussion
Once you have completed your experiments, you
are in a position to draw conclusions based on your
results. Specifically, you must attempt to interpret
your results in the context of the specific hypothesis
that you set out to address. Some of the issues to consider when making conclusions include:
Graphs, diagrams, drawings and photographs are
all called figures and should be numbered consecutively throughout a lab report or scientific paper. Each
figure is given a caption or title that describes its contents, giving enough information to allow the figure
to be self-explanatory. The graphs on this page and
on page 36 are labeled properly for you to refer to
later. Generally, the title of a figure is written above or
below the figure.
Tables are constructed in a similar way. Every
table should have a caption at the top which describes
the information displayed. The data (measurements of
your dependent variable) are listed in the body of the
What did you expect to find, and why?
How did your results compare with those
expected?
How might you explain unexpected results?
How might you test these potential explanations?
Should your hypothesis be modified?
Lab Assignment - Exercise 4
This assignment is to be handed in next week at the beginning of lab (before your quiz).
Each student must complete this assignment individually.
Last week you began working on your Osmosis Lab Report. You should have finished the Introduction
and Methods sections and begun construction of your graphs. Now that you have spent a lab period discussing
the scientific method and reviewing proper graph construction, you are ready to finish putting your lab report
together. Be sure that you review the Biology 107 Syllabus that explains how lab reports will be graded. Following directions is one of the most important objectives of the laboratory section of Biology 107 and lab reports
which are not properly constructed will lose points.
Make sure you re-read the instructions for completing your report (from last week’s Osmosis lab assignment). Refer to the Lab Manual Appendix and the Biology 107 web site (links page) for other helpful suggestions for how to write a good lab report.